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A Novel Chemo-inspired Genetic Algorithm for Economic Load Dispatch with Valve Point Loading Effect

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Proceedings of Fourth International Conference on Soft Computing for Problem Solving

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 335))

Abstract

The inherent drawback of the popular evolutionary algorithm as such genetic algorithm (GA) and also bio-inspired algorithm bacterial foraging optimization (BFO) lies in the fact that they very often suffer from the problem of being trapped into the local optimum. In recent past, various popular hybridized techniques of GA and BFO came out through different thought processes of the researches and have been implemented in the algorithm. Inspired by those ideas, in this paper, a novel approach has been opted for the hybridization of GA with BFO by incorporating chemotactic step as a local search operator at the end of the entire GA cycle; thus, the algorithm is named as chemo-inspired genetic algorithm (CGA) and it has also been extended for constrained optimization, and further it is named as CGAC, where “C” stands for being capable of handling constraints. At the outset, experiments are made to validate the superiority of CGAC over another hybrid method, namely LX-PM-C and H-LX-PM-C taking a set of 8 typical benchmark problems of various difficulty labels from the literature. Later, it has been applied to real-life application problem, where economic load dispatch (ELD) problem having 40 generators has been considered with valve point loading effect.

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Authors and Affiliations

  1. KIIT University, Bhubaneswar, Orissa, India

    Rajashree Mishra

  2. NIT Silchar, Silchar, Assam, India

    Kedar Nath Das

Authors
  1. Rajashree Mishra
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  2. Kedar Nath Das
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Correspondence to Rajashree Mishra .

Editor information

Editors and Affiliations

  1. Mathematics, National Institute of Technology Silchar, Silchar, Assam, India

    Kedar Nath Das

  2. Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, India

    Kusum Deep

  3. Department of Paper Technology, Indian Institute of Technology Roorkee, Roorkee, India

    Millie Pant

  4. Department of Mathematics, South Asian University, New Delhi, India

    Jagdish Chand Bansal

  5. Department of Computer Science, Liverpool Hope University, Liverpool, United Kingdom

    Atulya Nagar

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Mishra, R., Das, K.N. (2015). A Novel Chemo-inspired Genetic Algorithm for Economic Load Dispatch with Valve Point Loading Effect. In: Das, K., Deep, K., Pant, M., Bansal, J., Nagar, A. (eds) Proceedings of Fourth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 335. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2217-0_37

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  • DOI: https://doi.org/10.1007/978-81-322-2217-0_37

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2216-3

  • Online ISBN: 978-81-322-2217-0

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